Teaching courses

**In-Silico Learning (2020)***Introduction*: Storiographic introduction to learning and logic [Slides] Introduction to a theory of Learning for comparing Machine Learning algorithms with Data Mining ones [Comments].*Machine Learning*: Multilayer Neural Networks, Decision Trees and ν-Support Vector Machines. Comments, Code*Data Mining*: FPGrowth and Frequent Rule Mining. Slides, Code.

- Numerically Stable Collision Detection (2020)
- Topics:
**a)**Finite Numbers, IEEE754 floats, Machine Epsilon, Floating Point Arithmetic, Numerical Cancellation.**b)**Interval Arithmetic, Sphere-AABB Overlap Test in Interval Arithmetic.**c)**Separating Plane, Separating Axis, Separating Axis Theorem, Gottschalk’s Test for OBB Overlap: Naïf and Optimized test, Numerically robust Cross Product for the Separating Axis Theorem. - Slides, Source code

- Topics:
- Big-O Notation (2020)
- Topics:
**a.**Recursive Fibonacci, Bachmann–Landau notation, Binet’s Formula, Evaluating computational complexity by induction, Caching and Memoization, Linear Recurrences’ Theorem.**b.**Master Theorem, Cache-Aware Trees, VP-Trees. - Slides, Source code

- Topics:

- Web Programming Lab 1, 2017 (Prof. Ferretti)
*Topics*: Native types, casts, String, Scanner from System.in, Math, Count-controlled (for) and Condition-controlled (while) loops, Array and matrices, “Driver” programs.

- Databases: 2017, 2016 (Prof. Montesi)
*Topics*: Relational Algebra, SQL query language. DBMS Architecture: Query Plans, B+ Trees, Hashing, Transactions. Conceptual Data Modelling. RDBMS vs. Querying and Programming Languages.

- Complements of Databases, 2015 (Prof. Montesi)
- Business Intelligence for the Data Scientist - A tutorial on Data Warehouses

- Databases, 2015 (Prof. Montesi)
*Topics*: SQL query language. Conceptual Data Modelling. Querying and Programming Languages: Hibernate.

- Data Analysis, for a
*Complements of Databases*course